External Grid Research Articles

Microgrids with day-ahead energy forecasting for efficient energy management in smart grids: hybrid CS-RERNN

ABSTRACT By integrating smart grid technology with home energy management systems, households can monitor and optimise their energy consumption. This allows for more efficient use of energy resources, reducing waste and lowering energy bills. In this manuscript, a hybrid approach is proposed for smart grid home energy management with microgrids and day-ahead energy forecasts. The proposed control approach combines the Circle Search (CS) algorithm and Recalling-Enhanced Recurrent Neural Network (RERNN). Commonly it is named as CS-RERNN technique. The novelty of this paper is to optimise energy consumption and production within microgrids, thereby contributing to the overall efficiency of the smart grid system. The proposed method is used to reduce the electricity cost, peak-to-average ratio (PAR), and maximising consumer comfort. Energy management is performed based on the CS algorithm. A smart home connected to the external power grid (PG) is managed by the proposed method. Here, load demand is predicted by using RERNN. By then, the performance of the proposed method is implemented in MATLAB platform. The proposed method shows a high efficiency of 96%, and 22 $ of low electricity bill cost compared with other existing methods such as Particle swarm optimisation (PSO), Cuckoo search algorithm (CSA, and Border collie Optimisation (BCO).

An accelerated modelling method of full-bridge modular multilevel converter considering dead-time

To avoid short-circuits of the same side switching of power converters, the dead time is of significance in the pulse trigger gating signal for full bridge modular multilevel converter (FB-MMC). However, the previous equivalent models use the binary resistance switching model to equivalent the switching state which is impossible to simulate the switching with dead time, and the detailed model (DM) with higher levels is time-consuming and inefficient in electromagnetic transient (EMT) simulation. To address this problem, based on the state-space averaging method, a speed-up average value model (AVM) of FB-MMC considering dead time is proposed. Firstly, the working state of FB-MMC is obtained through analysing the switching states with dead time and is classified into three cases according to the capacitor. Secondly, derived from state-space equation, the three cases are integrated into a unified model by introducing the duty cycle, and then the equivalent controlled source is used as the interface circuit between the external grid and capacitor. Finally, a 49-level two-terminal MMC-HVDC system consisting of FB-MMC is constructed in PSCAD / EMTDC simulations, showing that the proposed AVM compared with DM has high accuracy and operation efficiency.

Calculation Method for the Transient Hot-Spot Temperature Rise of Oil-Immersed Bushing in High-Speed Railway

Traction oil-immersed bushing is the only channel for connecting the high-speed railway system with the external power grid, and its transient hot spot is one of the most important factors reflecting its operation status. Since the traction load of a high-speed railway has obvious impulse characteristics, the existing calculation method for bushing given in IEEE Std C57.19-100™-2012 is incompatible because it is designed for steady electrical loads. Thus, in this paper, the equivalent hot spot temperature rise of the bushing under varying traction loads is calculated by the traction parameters (i.e., operating time <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T_ot</i> , interval time <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T_it</i> , and per unit transient traction current <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I_tc</i> ). Then, the difference value of transient hot spot temperature rise is modified by analyzing the change of transient hot spot temperature rise under varying traction loads. Finally, a calculation method is proposed for the transient hot spot temperature rise of the oil-immersed bushing in high-speed railway under different traction loads. A case study of a 110 kV oil-immersed bushing shows that the proposed method is speedy and accurate.

Coordinated control and energy management combined with cyberattack identification in multi‐microgrid integrated with hybrid renewable‐storage

AbstractA comprehensive model is developed for coordinated control of voltage‐frequency‐inertia and identifying multiple cyberattacks simultaneously in two microgrids (MGs). The MGs are integrated with solar units, Wind turbine (WT), hybrid supercapacitor‐battery, and fuelcell. The MGs are modelled and controlled for operation under both an island and connected states. In the proposed method, a data centre is designed in which all the electrical and control signals related to the solar, wind, hybrid supercapacitor‐battery, and Fuel cell (FC) are collected, evaluated, and matched. The data centre comprises the following blocks: voltage‐frequency control, inertia control of WT, and identification of false data injection (FDI) cyberattacks on frequency, power, power/frequency, and voltage. The technique used in this article to identify FDI attacks is based on the real‐time method coupled with logical comparisons conducted in the time domain. This methodology provides prompt and precise detection, allowing for timely preventive measures and strategic responses. After FDI attacks occur, the implemented control system effectively manages and regulates the voltage and frequency at the desired levels, efficiently differentiating between ordinary functioning, faulty states, and potential cyber‐attacks. The unhealthy MG can transfer its load to the healthy MG for safety reasons. The healthy MG is then connected to the external grid and the synchronisation conditions are checked by the proposed control system. The results of the non‐linear simulation performed in MATLAB‐Simulink software confirm that the proposed model successfully operates and controls all resources (i.e. solar/wind/battery/FC), regulates the voltage/frequency under various loading conditions, and identifies FDI cyberattacks.

Possible improvements in effective fill factor using X-ray fluorescent interpixel reflectors.

The spatial resolution of energy-integrating diagnostic CT scanners is limited by interpixel reflectors on the detector, which optically isolate pixels but create dead space. Because the width of the reflector cannot easily be decreased, fill factor diminishes as resolution increases. We propose loading (or mixing) a high-Z element into the reflectors, causing the reflectors to be X-ray fluorescent. Re-emitted characteristic X-rays could be detected in adjacent pixels, increasing the effective fill factor and compensating for fill factor loss with higher-resolution detectors. The purpose of this work is to understand the physical principles of this approach and to analyze its effectiveness using Monte Carlo simulations. Detector pixels were modeled using the GEANT4 Monte Carlo package. The width of the reflector was kept constant at 0.1mm throughout, and we considered pixel pitches between 0.5 and 1mm. The pixelated scintillator material was gadolinium oxysulfide, 3mm thick. The baseline reflector material was chosen to be acrylic, and varying concentrations of a high-Z element were loaded into the material. We assumed that the optical characteristics of pixels were ideal (no absorption within pixels, perfect reflection at boundaries). The detector was irradiated uniformly with 10,000 X-ray photons to estimate its spectral response. The figure of merit was the variance of the detector signal at zero frequency normalized to that of an ideal single-bin photon-counting detector with 100% fill factor. Sensitivity analyses were conducted to understand the effect of varying the high-Z element concentration and the spectrum. Initial simulations suggested that a k-edge near 50keV would be ideal. Gd was therefore selected as the high-Z material. The relative variances for a conventional energy integrating detector without Gd at 1mm pixel pitch (81% fill factor) and 0.5mm pixel pitch (64% fill factor) were 1.38 and 1.74, compared to 1.00 for an ideal photon counting detector, implying a 26% variance penalty for 0.5mm pitch. When 1g/cm3 Gd was loaded into the interpixel reflector, the relative variance improved to 1.27 and 1.43, respectively, implying that the variance penalty for including Gd together with 0.5mm pitch is only 4%. Performance was nearly maximized at 1.0g/cm3 of Gd, but a concentration of 0.5g/cm3 of Gd showed most of the benefit. Improvements depend weakly on kV, with lower kV associated with higher improvements. An external anti-scatter grid was not modeled in our simulations and would reduce the expected benefit, depending greatly on the pitch and dimensionality of the anti-scatter grid. The losses in fill factor associated with smaller pixel pitch can be reduced if Gd or a similar element could be loaded into the interpixel reflector. These improvements in noise efficiency are yet to be verified experimentally.

Wind generation in weak systems

Control systems of wind generators are usually designed neglecting the effect of the external grid (the impedance of the grid is much smaller than the impedance of the step-up transformers). Wind generator manufacturers are facing considerable challenges when connecting their machines to weak systems. A number of issues may arise. This paper classifies them and proposes a common approach to address them.

Local sustainable communities: Sector coupling and community optimization in decentralized energy systems

Achieving local sustainable development often depends on consumers' incentives to efficiently utilize energy and resources. In this paper, Local sustainable communities (LSC) are introduced as a combination of sustainable communities and local energy communities to promote local energy and resource utilization. Business models on technology and service provision and those on promoting sustainable resource utilization are developed, which are then applied to a community in Austria. A modeling framework on sector coupling in community operations, that also considers resource utilization is developed to assess the impact of the business models. LSC business models promote participation and sustainable operation in an LSC as 31% of electricity and 34% of heat can be covered by LSC purchase. The implementation of energy recovery business models and the availability of sufficient decentralized technologies have the greatest impact on LSC operations, reducing external electricity grid coverage to 58%. The consideration of resource business models can positively contribute to a local resource utilization efficiency, reducing the water pipeline coverage by 43%. The introduction of an LSC has a positive impact on the United Nations Sustainable Development Goals and can therefore efficiently contribute to the development of a cleaner energy system.

Dynamic optimisation of unbalanced distribution network management by model predictive control with Markov reward processes

In this work, a two-level control system is used to minimize the total active power losses of an active distribution system connected to the external grid and composed of a wind turbine, two photovoltaic power sources, and two batteries. At the first control level, a model-based predictive control (MPC) is run, using non-homogeneous Markov reward models for wind power prediction and homogeneous Markov reward models for photovoltaic power. At the second level, an algorithm is run for optimal management of voltage control assets, such as voltage regulating transformers, to minimize losses. Different scenarios have been considered, highlighting the advantages of using an MPC framework. This results in an optimization process that can be influenced by different time horizons depending on whether or not the MPC is applied. The predictions allow considering a long-horizon stepwise optimization process that leads to an increasing number of variables along with the decrease of total active power losses. When the MPC is not applied, a short-horizon analysis is performed with a decrease in both the number of variables and the quality of the results. Different cases are considered in which the nominal power of a photovoltaic unit and the battery capacity are modified.

Enhancing Stability of Grid-Supporting Inverters from an Analytical Point of View with Lessons from Microgrids

The central components influencing future grid stability in the future are inverters and their controllers. This paper delves into the pivotal role of inverters and their controllers in shaping the future stability of grids. Focusing on grid-supporting inverters, the study utilizes a microgrid test setup to explore their impact on overall grid stability. Employing impedance-based stability analysis with the Nyquist criterion, the paper introduces variations in internal inverter parameters and external grid parameters using pole-zero map considerations. The inverter’s control structure, resembling standard generators with droop control, facilitates the application of grid operators’ knowledge to inverter control. Mathematical insights into stability principles are provided, highlighting the influence of poles related to the phase-locked loop and the strategic placement of additional poles for enhanced stability. Furthermore, the paper evaluates the effects of rotating inertia, revealing that a 50% increase in system inertia can stabilize unstable microgrid behavior, enabling grid-supporting inverters to actively contribute to grid reliability.

Power load analysis and configuration optimization of solar thermal-PV hybrid microgrid based on building

Solar thermal power system and photovoltaic coupled system can supply electric energy based on renewable solar energy. To explore the optimal configuration of hybrid microgrid driven by solar energy and to achieve a stable and sufficient electric power supply for the distributed energy system, this paper configures a solar thermal-photovoltaic hybrid microgrid and compares the performance of several microgrids based on the power load analysis of the building. The working fluid and the microgrid configuration are determined based on the performance evaluation of single and hybrid microgrids. The effect of solar irradiation on economic and environmental performance is analyzed under the meteorological data of Xi'an and Lhasa in China. Furthermore, the configuration optimizations of a hybrid microgrid based on the actual load and basic load of the building are carried out to examine the performance of the system. Results indicate that economic and environmental performances are sensitive to solar irradiation. More than 50 % of the area of solar thermal collector can be saved for Lhasa compared with Xi'an. Solar thermal-photovoltaic hybrid microgrid with battery can decrease carbon emission and avoid dependence on the external power grid.

The potential of multiapartment rooftop PV systems as citizen’ energy communities in Latvia

Electricity generation from photovoltaic (PV) in Latvia is currently below the necessary capacity required to contribute to achieving climate neutrality by 2050. However, photovoltaic offer households and companies the opportunity to align their electricity consumption with environmental goals while supporting the European Green Deal objectives. In recent years, there was a growing interest in the installation of photovoltaic microgenerators in Latvia. By June 2023, the total number of households microgenerators connected to the grid has reached 15,000, boasting a collective production capacity exceeding 120 MW. This significant increase is in stark contrast to the situation 5 years ago when Latvia had a mere 3 MW of photovoltaic capacity. Several factors contributed to this growth, including a surge in electricity prices, at times surging more than tenfold, and the implementation of renewable energy (RE) use support measures to facilitate the acquisition of RE systems. Furthermore, 2023 witnessed numerous amendments to Latvia’s energy policy documents and the introduction of the concept of citizen energy communities (CEC), indicating a growing emphasis on harnessing solar energy potential in the country. However, it remains crucial to base these endeavors on accurate, economically viable information regarding solar technologies, their costs and their anticipated long-term outcomes. This manuscript aims to provide an overview of the grid-connected potential of rooftop photovoltaic systems within a Latvian urban setting. Through extensive research, a model has been developed, employing a thoroughly tested simulation program for evaluating the generation capacity of photovoltaic systems. This model considers real electricity consumption data, the existing infrastructure and economic factors. The findings affirm the technical and economic viability of urban rooftop photovoltaic systems within the Latvian context. It has been established that the implementation of such citizen energy communities energy systems holds significant potential. These systems have the potential to be a promising solution for future electricity generation, addressing some of the demands while relieving strain on external power grids. However, the full potential can only be realized with improved infrastructure, and the system’s profitability is heavily contingent on market dynamics and political conditions. This study may also be applicable to other photovoltaic systems facing similar climate conditions.

A battery-to-electrolyzer pathway for energy management in a hybrid battery/hydrogen microgrid

A RES-based microgrid with two simultaneous storage options - battery and hydrogen - is considered. While the battery pack serves as a short-term storage solution, the hydrogen-cycle (consisting of an electrolyzer, a hydrogen pressurized tank and a fuel cell stack) provides for a long-term (seasonal) storage in order to improve the system resilience and to allow off-grid operation for longer time. With respect to the most classical energy management approach, where energy is transferred either from PV to battery (as the priority transfer) or from PV to electrolyzer, the novel strategy adopted in this paper also adds the possibility of a battery-to-electrolyzer energy conversion route. This route is enabled whenever the energy stored in the battery is expected to overcome the estimated short-term energy needs. The novel strategy reveals significant potential to increase the hydrogen production during the summer months, by redirecting to the electrolyzer part of the excess energy that would be otherwise curtailed or transferred to an external grid. Application of the strategy during autumn and winter time reveals on the contrary a clear worsening of the microgrid performance and should be avoided.

An efficient mixed-variable generation operator for integrated energy system configuration optimization

Energy consumption has skyrocketed as society has progressed, resulting in energy crises and environmental issues. New energy technologies are being developed to address these challenges, and technologies such as the cogeneration of electricity, heating, and cooling are being used to improve energy utilization. The configuration of an energy system has a critical impact on the economics of the system, its ability to supply energy, etc. This study establishes a multiobjective mixed-variable configuration optimization model for a comprehensive combined cooling, heating, and power energy system. The model considers equipment types (categorical variables), equipment quantities (integer variables), and critical parameters (real variables) as optimization variables, where economic performance, the proportion of renewable energy, supply shortage, and dependence on the external power grid are considered unoptimized objectives. This is a multiobjective and mixed-variable problem, and the combination of the two properties poses an excellent challenge for evolutionary algorithms in optimizing the model. Therefore, we propose an efficient generating operator based on a fully connected weighted neural network, called the FCWN operator. This operator overcomes the challenge of the discrete variable space and broken neighborhood relationships in mixed-variable problems. During the algorithm search process, search history information is used to update the fully connected weight network for distribution estimation of the variable space. Offspring are generated based on the fully connected network to improve the algorithm’s search efficiency. In the experimental section, we construct a model with 20 variables and conduct simulation-based configuration optimization for scenarios with 3, 5, and 8 available equipment types. The final obtained Pareto frontier solution set is evaluated using the hypervolume metric, a widely used multiobjective evaluation metric. The Wilcoxon rank sum test on the experimental results shows that the proposed algorithm has better results than other state-of-the-art algorithms at a 95% confidence level.

A self-driven solar air heater integrated with a thermal energy storage unit: Design and experiment study

The Self-driven solar air heater (SDSAH) can operate independently without reliance on an external power grid through the incorporation of photovoltaic (PV) panels, however it is still subject to intermittent operation and large temperature fluctuations. In this study, a novel SDSAH integrated with a thermal energy storage (TES) unit was proposed and the operational thermal and electrical performance of the SDSAH with TES unit were experimentally investigated. The results showed that the SDSAH could output heat continuously throughout the day (24 h) in a self-sustaining mode and automatically adjust the airflow rate according to solar irradiance. The overall thermal efficiency of this system averages at 52.73 % throughout the day. The introduction of the TES unit could lower the peak temperature of the outlet air by more than 9 K and improve the electrical efficiency of PV panels. However, due to heat loss at night, the whole-day thermal efficiency will be slightly lower than that of SDSAH without a TES unit. The energy payback time for this system was 42 months. This study offers new ideas and solutions for a distributed agricultural drying system.

Distribution Network Reconfiguration Considering the Impacts of Local Renewable Generation and External Power Grid

Distribution Network Reconfiguration Considering the Impacts of Local Renewable Generation and External Power Grid

Asynchronous generator replacement scheme with internal capacitive reactive power compensation

The relevance of using compensated induction machines in the generator mode of autonomous power supply systems is determined by their ability to provide a stable and reliable power supply even in the absence of an external grid. The research aims to develop a procedure for determining the characteristics of an equivalent circuit of compensated induction generators that considers the mutual influence between the main and additional phase windings of the armature. The theory of an idealised induction machine with the representation of electromechanical energy conversion processes and basic physical parameters in the form of equations of electrical equilibrium and drive motion was used to obtain the calculated characteristics of the generator’s operating modes of this class. The generalised system of differential equations made it possible to calculate dynamic and static processes for symmetrical and asymmetrical modes at given machine parameters under different methods of excitation and voltage stabilisation under variable load. For the practical implementation of modelling the parameters of an induction generator, the equations of electrical equilibrium of the stator and rotor circuits for the symmetrical steady-state mode are used, which is a special case of the generalised mathematical model of the machine for both transient and steady-state processes with constant parameters of the substitution scheme. Consideration of the structural and functional features of compensated induction generators was made possible by using a mathematical model with the armature winding divided into two coaxial or spatially offset half-windings. In this case, the number of calculation equations doubles. The use of an autotransformer scheme for switching on the stator phase half-windings to capacitors required the introduction of an additional differential equation for the electrical equilibrium of the stator phases. This made it possible to substantiate the values of active and inductive resistances used in the replacement circuit of an induction generator with internal capacitive reactive power compensation. The mutual inductive coupling of the main and additional half-windings of the generator stator phase windings due to both the operating magnetic flux and the magnetic fluxes of dissipation was considered. The practical significance of the obtained results is to increase the efficiency and stability of the power supply, which helps to reduce losses and improve the operation of electric power systems

Solar parking lot management: An IoT platform for smart charging EV fleets, using real-time data and production forecasts

The fast transition to the electrification of the energy system, combined with an exponential growth of the market share of electric vehicles, is leading to a tight interrelation between electric energy production and transportation, two prominent sectors in fossil fuels consumption and greenhouse gas emissions. Accelerating this process, the management of electric fluxes, aiming at optimizing production and demand coupling, plays a crucial role in reaching the net-zero emission target. The proposed software platform is designed to optimally manage the energy fluxes for a solar powered parking lot, serving a fleet of electric vehicles; the real-time knowledge of energy production and demand, in conjunction with forecasted power generation, allows the maximization of renewable energy self-consumption, thus reducing the exchange with the external grid. The software platform can work either in design mode, allowing the dimensioning of the various parking lot components, or in real-time mode managing instantaneously the energy balance. As a case study, it is tested on the 2019 parking lot mobility data of a research center, assuming a complete transformation of the then existing fleet of employees' cars to electric vehicles. A comparison of the resulting energy flows with those projected by an established commercial tool is performed, as well as a preliminary economic evaluation. Both consistency of the simulation results and favorable economics validate the presented smart charging algorithm and Internet of Things platform for the real-time energy management of a solar parking lot.

Optimal allocation of hybrid energy storage capacity of DC microgrid based on model predictive control algorithm

To effectively enhance the safety, stability, and economic operation capability of DC microgrids, an optimized control strategy for DC microgrid hybrid energy storage system (HESS)(The abbreviation table is shown in Table 2) based on model predictive control theory is proposed. Based on the characteristics of supercapacitors and batteries, system safety requirements, and various constraints, a predictive model for a hybrid energy storage DC microgrid is established. By defining its optimization indicators, designing an energy optimization management strategy, and transforming it into a quadratic programming problem for solution, the reasonable scheduling of power in the DC microgrid has been achieved. In addition, a power control method was proposed for the system without constraints. The simulation experiment results show that at the initial sampling time, the system operates normally, and the MPC algorithm allocates two types of energy storage devices to discharge to meet the net load demand, without absorbing electricity from the external network. At the 30th sampling point, the net load increases, and the MPC controller obtains the optimal solution of the control problem based on the known net load prediction data at the previous sampling time. It outputs the operating reference values of each output unit at the next time. Starting from the 100th to 199th sampling points, SOC UC falls below the lower limit of the safety interval, and the system enters situation 4 mode. The external network output assists the battery in working. At the 131st sampling point, the net load decreases, the system enters Situation 3 mode, and the battery operates independently. Until the 179th point, SOC B was also below the lower limit of its safety interval, and the system entered situation 5 mode, completely maintaining system power balance by external network power. Starting from point 201, the net load becomes negative, and the system charges the HESS according to instructions and stops the external power grid energy transmission. Conclusion: The feasibility and effectiveness of the proposed optimization management strategy have been verified.

Development of control strategy for community battery energy storage system in grid-connected microgrid of high photovoltaic penetration level

The focus of this paper is to develop a control strategy for a community battery bank in a grid-connected microgrid in which a significant level of photovoltaic generation is embedded. In order to minimize the capacity of the community battery, the power transfer capacity of the interconnection link between the microgrid and the external grid system is utilized to safe maximum levels. Through Empirical Mode Decomposition analysis of the net power flows of the microgrid, the daily and seasonal modes of the net power oscillations are identified as the two dominant low-frequency components. Whence a rule-based operational strategy is developed to control the power flows of the community battery via a novel dynamic referencing scheme for the state-of-charge of the battery bank. The battery control scheme counteracts the dominant daily and seasonal modes of oscillations of the net power. The numerical calculations performed for a case study shows that the proposed scheme leads to an approximately 16% decrease in the required battery capacity for particular growth rate of solid-electrolyte interphase film in the battery bank. The scheme does not require the forecasting of the net power, and thus, it has an increased degree of robustness when the community battery undertakes the power buffering task.

Multi-criteria decision analysis for the planning of island microgrid system: A case study of Yongxing island, China

Remote island communities often struggle to meet energy needs affordably, sustainably, and reliably. Island microgrid (IM) systems offer a promising solution; however, optimal planning considering diverse components and alternatives remains challenging. Using China's Yongxing Island as a case study, we propose a novel indicator system integrating economic, resilience, energy, and environmental dimensions. The indicator system is integrated with the HOMER Pro software and the reference point method to identify the optimal energy configuration of Yongxing Island's IM system. Moreover, a comprehensive uncertainty analysis is conducted on the optimal configuration to reveal how optimal configuration results change relative to changes in energy demand, energy prices, and investment costs of technologies and to demonstrate how the system would cope with disturbance. To meet Yongxing Island's 2030 energy demand (including electricity, thermal, and hydrogen), the best energy configuration scheme for the microgrid is the combination of photovoltaic panels, wind turbines, diesel generators, energy storage batteries, external grid, electrolyzers, diesel reformers, hydrogen tanks, thermal load controllers, boilers, and power converters. Moreover, wind turbines dominate power supply and would change the sizing and hourly power generation under uncertainties. Thermal demand relies on thermal load controllers, while electrolyzers and diesel reformers address hydrogen demand.